name: infra-engineer description: "Comprehensive infrastructure engineering covering DevOps, cloud platforms, FinOps, and DevSecOps. Platforms: AWS (EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation), Azure basics, Cloudflare (Workers, R2, D1, Pages), GCP (GKE, Cloud Run, Cloud Storage), Docker, Kubernetes. Capabilities: CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), GitOps, infrastructure as code (Terraform, CloudFormation), container orchestration, cost optimization, security scanning, vulnerability management, secrets management, compliance (SOC2, HIPAA). Actions: deploy, configure, manage, scale, monitor, secure, optimize cloud infrastructure. Keywords: AWS, EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation, Azure, Kubernetes, k8s, Docker, Terraform, CI/CD, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, cost optimization, FinOps, reserved instances, spot instances, security scanning, SAST, DAST, vulnerability management, secrets management, Vault, compliance, monitoring, observability. Use when: deploying to AWS/Azure/GCP/Cloudflare, setting up CI/CD pipelines, implementing GitOps workflows, managing Kubernetes clusters, optimizing cloud costs, implementing security best practices, managing infrastructure as code, container orchestration, compliance requirements, cost analysis and optimization." license: MIT version: 2.0.0

Infrastructure Engineering Skill

Comprehensive guide for modern infrastructure engineering covering DevOps practices, multi-cloud platforms (AWS, Azure, GCP, Cloudflare), FinOps cost optimization, and DevSecOps security practices.

When to Use This Skill

Use this skill when:

• DevOps: Setting up CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), implementing GitOps workflows (ArgoCD, Flux)
• AWS: Deploying to EC2, Lambda, ECS, EKS, managing S3, RDS, using CloudFormation/CDK
• Azure: Working with Azure VMs, App Service, AKS, Azure Functions, Storage Accounts
• GCP: Managing Compute Engine, GKE, Cloud Run, Cloud Storage, App Engine
• Cloudflare: Deploying Workers, R2 storage, D1 databases, Pages applications
• Kubernetes: Managing clusters, deployments, services, ingress, Helm charts, operators
• Docker: Containerizing applications, multi-stage builds, Docker Compose, registries
• FinOps: Analyzing cloud costs, optimizing spend, reserved instances, spot instances, rightsizing
• DevSecOps: Security scanning (SAST/DAST), vulnerability management, secrets management, compliance
• IaC: Terraform, CloudFormation, Pulumi, configuration management
• Monitoring: Setting up observability, logging, metrics, alerting, distributed tracing

Platform Selection Guide

When to Use AWS

Best For:

• General-purpose cloud computing at scale
• Mature ecosystem with 200+ services
• Enterprise workloads with compliance requirements
• Hybrid cloud with AWS Outposts
• Extensive third-party integrations
• Advanced networking and security controls

Key Services:

• EC2 (virtual machines, flexible compute)
• Lambda (serverless functions, event-driven)
• ECS/EKS (container orchestration)
• S3 (object storage, industry standard)
• RDS (managed relational databases)
• DynamoDB (NoSQL, global tables)
• CloudFormation/CDK (infrastructure as code)
• IAM (identity and access management)
• VPC (virtual private cloud networking)

Cost Profile: Pay-as-you-go, reserved instances (up to 72% discount), savings plans, spot instances (up to 90% discount)

When to Use Azure

Best For:

• Microsoft-centric organizations (.NET, Active Directory)
• Hybrid cloud scenarios (Azure Arc, Stack)
• Enterprise agreements with Microsoft
• Windows Server and SQL Server workloads
• Integration with Microsoft 365 and Dynamics
• Strong compliance certifications (90+ certifications)

Key Services:

• Virtual Machines (Windows/Linux compute)
• App Service (PaaS for web apps)
• AKS (managed Kubernetes)
• Azure Functions (serverless compute)
• Storage Accounts (Blob, File, Queue, Table)
• SQL Database (managed SQL Server)
• Active Directory (identity management)
• ARM Templates/Bicep (infrastructure as code)

Cost Profile: Pay-as-you-go, reserved instances, Azure Hybrid Benefit for Windows/SQL Server licenses

When to Use Cloudflare

Best For:

• Edge-first applications with global distribution
• Ultra-low latency requirements (<50ms)
• Static sites with serverless functions
• Zero egress cost scenarios (R2 storage)
• WebSocket/real-time applications (Durable Objects)
• AI/ML at the edge (Workers AI)

Key Products:

• Workers (serverless functions)
• R2 (object storage, S3-compatible)
• D1 (SQLite database with global replication)
• KV (key-value store)
• Pages (static hosting + functions)
• Durable Objects (stateful compute)
• Browser Rendering (headless browser automation)

Cost Profile: Pay-per-request, generous free tier, zero egress fees

When to Use Kubernetes

Best For:

• Container orchestration at scale
• Microservices architectures with 10+ services
• Multi-cloud and hybrid deployments
• Self-healing and auto-scaling workloads
• Complex deployment strategies (blue/green, canary)
• Service mesh architectures (Istio, Linkerd)
• Stateful applications with operators

Key Features:

• Declarative configuration (YAML manifests)
• Automated rollouts and rollbacks
• Service discovery and load balancing
• Self-healing (restarts failed containers)
• Horizontal pod autoscaling
• Secret and configuration management
• Storage orchestration
• Batch job execution

Managed Options: EKS (AWS), AKS (Azure), GKE (GCP), managed k8s providers

Cost Profile: Cluster management fees + node costs (optimize with spot instances, cluster autoscaling)

When to Use Docker

Best For:

• Local development consistency
• Microservices architectures
• Multi-language stack applications
• Traditional VPS/VM deployments
• Foundation for Kubernetes workloads
• CI/CD build environments
• Database containerization (dev/test)

Key Capabilities:

• Application isolation and portability
• Multi-stage builds for optimization
• Docker Compose for multi-container apps
• Volume management for data persistence
• Network configuration and service discovery
• Cross-platform compatibility (amd64, arm64)
• BuildKit for improved build performance

Cost Profile: Infrastructure cost only (compute + storage), no orchestration overhead

When to Use Google Cloud

Best For:

• Enterprise-scale applications
• Data analytics and ML pipelines (BigQuery, Vertex AI)
• Hybrid/multi-cloud deployments
• Kubernetes at scale (GKE)
• Managed databases (Cloud SQL, Firestore, Spanner)
• Complex IAM and compliance requirements

Key Services:

• Compute Engine (VMs)
• GKE (managed Kubernetes)
• Cloud Run (containerized serverless)
• App Engine (PaaS)
• Cloud Storage (object storage)
• Cloud SQL (managed databases)

Cost Profile: Varied pricing, sustained use discounts, committed use contracts

Quick Start

AWS Lambda Function

# Install AWS CLI
curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip && sudo ./aws/install

# Configure credentials
aws configure

# Create Lambda function with SAM
sam init --runtime python3.11
sam build && sam deploy --guided

See: references/aws-lambda.md

AWS EKS Kubernetes Cluster

# Install eksctl
brew install eksctl  # or curl download

# Create cluster
eksctl create cluster \
  --name my-cluster \
  --region us-west-2 \
  --nodegroup-name standard-workers \
  --node-type t3.medium \
  --nodes 3 \
  --nodes-min 1 \
  --nodes-max 4

See: references/kubernetes-basics.md

Azure Deployment

# Install Azure CLI
curl -L https://aka.ms/InstallAzureCli | bash

# Login and create resources
az login
az group create --name myResourceGroup --location eastus
az webapp create --resource-group myResourceGroup \
  --name myapp --runtime "NODE:18-lts"

See: references/azure-basics.md

Cloudflare Workers

# Install Wrangler CLI
npm install -g wrangler

# Create and deploy Worker
wrangler init my-worker
cd my-worker
wrangler deploy

See: references/cloudflare-workers-basics.md

Kubernetes Deployment

# Create deployment
kubectl create deployment nginx --image=nginx:latest
kubectl expose deployment nginx --port=80 --type=LoadBalancer

# Apply from manifest
kubectl apply -f deployment.yaml

# Check status
kubectl get pods,services,deployments

See: references/kubernetes-basics.md

Docker Container

# Create Dockerfile
cat > Dockerfile <<EOF
FROM node:20-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --production
COPY . .
EXPOSE 3000
CMD ["node", "server.js"]
EOF

# Build and run
docker build -t myapp .
docker run -p 3000:3000 myapp

See: references/docker-basics.md

Reference Navigation

AWS (Amazon Web Services)

• aws-overview.md - AWS fundamentals, account setup, IAM basics
• aws-ec2.md - EC2 instances, AMIs, security groups, auto-scaling
• aws-lambda.md - Serverless functions, SAM, event sources, layers
• aws-ecs-eks.md - Container orchestration, ECS vs EKS, Fargate
• aws-s3-rds.md - S3 storage, RDS databases, backup strategies
• aws-cloudformation.md - Infrastructure as code, CDK, best practices
• aws-networking.md - VPC, subnets, security groups, load balancers

Azure (Microsoft Azure)

• azure-basics.md - Azure fundamentals, subscriptions, resource groups
• azure-compute.md - VMs, App Service, AKS, Azure Functions
• azure-storage.md - Storage Accounts, Blob, Files, managed disks

Cloudflare Platform

• cloudflare-platform.md - Edge computing overview, key components
• cloudflare-workers-basics.md - Getting started, handler types, basic patterns
• cloudflare-workers-advanced.md - Advanced patterns, performance, optimization
• cloudflare-workers-apis.md - Runtime APIs, bindings, integrations
• cloudflare-r2-storage.md - R2 object storage, S3 compatibility, best practices
• cloudflare-d1-kv.md - D1 SQLite database, KV store, use cases
• browser-rendering.md - Puppeteer/Playwright automation on Cloudflare

Kubernetes & Container Orchestration

• kubernetes-basics.md - Core concepts, pods, deployments, services
• kubernetes-advanced.md - StatefulSets, operators, custom resources
• kubernetes-networking.md - Ingress, service mesh, network policies
• helm-charts.md - Package management, charts, repositories

Docker Containerization

• docker-basics.md - Core concepts, Dockerfile, images, containers
• docker-compose.md - Multi-container apps, networking, volumes
• docker-security.md - Image scanning, secrets, best practices

Google Cloud Platform

• gcloud-platform.md - GCP overview, gcloud CLI, authentication
• gcloud-services.md - Compute Engine, GKE, Cloud Run, App Engine

CI/CD & GitOps

• cicd-github-actions.md - GitHub Actions workflows, runners, secrets
• cicd-gitlab.md - GitLab CI/CD pipelines, artifacts, caching
• gitops-argocd.md - ArgoCD setup, app of apps pattern, sync policies
• gitops-flux.md - Flux controllers, GitOps toolkit, multi-tenancy

FinOps (Cost Optimization)

• finops-basics.md - Cost optimization principles, FinOps lifecycle
• finops-aws.md - AWS cost optimization, RI, savings plans, spot
• finops-azure.md - Azure cost management, reservations, hybrid benefit
• finops-gcp.md - GCP cost optimization, committed use, sustained use
• finops-tools.md - Cost analysis tools, Kubecost, CloudHealth, Infracost

DevSecOps (Security)

• devsecops-basics.md - Security best practices, shift-left security
• devsecops-scanning.md - SAST, DAST, SCA, container scanning
• secrets-management.md - Vault, AWS Secrets Manager, sealed secrets
• compliance.md - SOC2, HIPAA, PCI-DSS, audit logging

Infrastructure as Code

• terraform-basics.md - Terraform fundamentals, providers, state
• terraform-advanced.md - Modules, workspaces, remote state
• cloudformation-basics.md - CloudFormation templates, stacks, change sets

Utilities & Scripts

• scripts/cloudflare-deploy.py - Automate Cloudflare Worker deployments
• scripts/docker-optimize.py - Analyze and optimize Dockerfiles
• scripts/cost-analyzer.py - Cloud cost analysis and reporting
• scripts/security-scanner.py - Automated security scanning

Common Workflows

Multi-Cloud Architecture

# Edge Layer: Cloudflare Workers (global routing, caching)
# Compute Layer: AWS ECS/Lambda or Azure App Service (application logic)
# Data Layer: AWS RDS or Azure SQL (persistent storage)
# CDN/Storage: Cloudflare R2 or AWS S3 (static assets)

Benefits:
- Best-of-breed services per layer
- Geographic redundancy
- Cost optimization across providers

AWS ECS Deployment with CI/CD

# GitHub Actions workflow
name: Deploy to ECS
on: push
jobs:
  deploy:
    - Build Docker image
    - Push to ECR
    - Update ECS task definition
    - Deploy to ECS service
    - Wait for deployment stabilization

Kubernetes GitOps with ArgoCD

# Git repository structure
/apps
  /production
    - deployment.yaml
    - service.yaml
    - ingress.yaml
  /staging
    - deployment.yaml

# ArgoCD syncs cluster state from Git
# Changes: Git commit → ArgoCD detects → Auto-sync to cluster

Multi-Stage Docker Build

# Build stage
FROM node:20-alpine AS build
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Production stage
FROM node:20-alpine
WORKDIR /app
COPY --from=build /app/dist ./dist
COPY --from=build /app/node_modules ./node_modules
USER node
CMD ["node", "dist/server.js"]

FinOps Cost Optimization Workflow

# 1. Discovery: Identify untagged resources
# 2. Analysis: Right-size instances (CPU/memory utilization)
# 3. Optimization:
#    - Convert to reserved instances (predictable workloads)
#    - Use spot instances (fault-tolerant workloads)
#    - Schedule start/stop (dev environments)
# 4. Monitoring: Set budget alerts, track savings
# 5. Governance: Enforce tagging policies

DevSecOps Security Pipeline

# 1. Code Commit
# 2. SAST Scan: SonarQube, Semgrep (static code analysis)
# 3. Dependency Check: Snyk, Trivy (vulnerability scanning)
# 4. Build: Docker image
# 5. Container Scan: Trivy, Grype (image vulnerabilities)
# 6. DAST Scan: OWASP ZAP (runtime security testing)
# 7. Deploy: Only if all scans pass
# 8. Runtime Protection: Falco, AWS GuardDuty

Terraform Infrastructure Deployment

# 1. Write: Define infrastructure in .tf files
# 2. Init: terraform init (download providers)
# 3. Plan: terraform plan (preview changes)
# 4. Apply: terraform apply (create/update resources)
# 5. State: Store state in S3 with DynamoDB locking
# 6. Modules: Reuse common patterns across environments

Best Practices

DevOps

• CI/CD: Automate testing and deployment, use feature flags for progressive rollouts
• GitOps: Declarative infrastructure, Git as single source of truth, automated sync
• Monitoring: Implement observability (logs, metrics, traces), set up alerting
• Incident Management: Runbooks, postmortems, blameless culture
• Automation: Infrastructure as code, configuration management, self-service platforms

Security (DevSecOps)

• Shift Left: Security scanning early in pipeline (SAST, dependency checks)
• Secrets Management: Use Vault, AWS Secrets Manager, or sealed secrets (never in code/Git)
• Container Security: Run as non-root, minimal base images, regular scanning
• Network Security: Zero-trust architecture, service mesh, network policies
• Access Control: Least privilege IAM, MFA, temporary credentials
• Compliance: Audit logging, encryption at rest/transit, regular security reviews
• Runtime Protection: Security monitoring, intrusion detection, automated response

Cost Optimization (FinOps)

• Tagging: Enforce resource tagging for cost allocation and tracking
• Rightsizing: Analyze utilization, downsize over-provisioned resources
• Reserved Capacity: Purchase RI/savings plans for predictable workloads (up to 72% discount)
• Spot/Preemptible: Use for fault-tolerant workloads (up to 90% discount)
• Scheduling: Auto-stop dev/test environments during off-hours
• Storage Optimization: Lifecycle policies, archive to cheaper tiers, delete orphaned resources
• Monitoring: Budget alerts, cost anomaly detection, chargeback/showback
• Governance: Approval workflows for expensive resources, quota management

Kubernetes

• Resource Management: Set requests/limits, use horizontal pod autoscaling
• High Availability: Multi-zone clusters, pod disruption budgets, anti-affinity rules
• Security: RBAC, pod security policies, network policies, admission controllers
• Observability: Prometheus metrics, distributed tracing, centralized logging
• GitOps: ArgoCD/Flux for declarative deployments, automatic drift correction

Performance

• Compute: Auto-scaling, load balancing, multi-region for low latency
• Caching: CDN, in-memory caching (Redis/Memcached), edge computing
• Storage: Choose appropriate tier (SSD vs HDD), enable caching, CDN for static assets
• Containers: Multi-stage builds, minimal images, layer caching
• Databases: Connection pooling, read replicas, query optimization, indexing

Development

• Local Development: Docker Compose for consistent environments, dev containers
• Testing: Unit, integration, end-to-end tests in CI/CD pipeline
• Infrastructure as Code: Terraform/CloudFormation for repeatability
• Documentation: Architecture diagrams, runbooks, API documentation
• Version Control: Git for code and infrastructure, semantic versioning

Decision Matrix

Resources

Cloud Providers

• AWS Docs: https://docs.aws.amazon.com
• Azure Docs: https://docs.microsoft.com/azure
• GCP Docs: https://cloud.google.com/docs
• Cloudflare Docs: https://developers.cloudflare.com

Container & Orchestration

• Docker Docs: https://docs.docker.com
• Kubernetes Docs: https://kubernetes.io/docs
• Helm: https://helm.sh/docs

CI/CD & GitOps

• GitHub Actions: https://docs.github.com/actions
• GitLab CI: https://docs.gitlab.com/ee/ci/
• ArgoCD: https://argo-cd.readthedocs.io
• Flux: https://fluxcd.io/docs

Infrastructure as Code

• Terraform: https://developer.hashicorp.com/terraform
• AWS CDK: https://docs.aws.amazon.com/cdk
• Pulumi: https://www.pulumi.com/docs

Security & Compliance

• OWASP: https://owasp.org
• CIS Benchmarks: https://www.cisecurity.org/cis-benchmarks
• HashiCorp Vault: https://developer.hashicorp.com/vault

FinOps & Cost Optimization

• FinOps Foundation: https://www.finops.org
• AWS Cost Optimization: https://aws.amazon.com/pricing/cost-optimization
• Kubecost: https://www.kubecost.com

Implementation Checklist

AWS Lambda Deployment

• Install AWS CLI and SAM CLI
• Configure AWS credentials (access key, secret key)
• Create Lambda function with SAM template
• Configure IAM role and policies
• Test locally with sam local invoke
• Deploy with sam deploy
• Set up CloudWatch monitoring and alarms

AWS EKS Kubernetes Cluster

• Install kubectl, eksctl, aws-cli
• Configure AWS credentials
• Create EKS cluster with eksctl
• Configure kubectl context
• Install cluster autoscaler
• Set up Helm for package management
• Deploy applications with kubectl/Helm
• Configure ingress controller (ALB/NGINX)

Azure Deployment

• Install Azure CLI
• Login with az login
• Create resource group
• Deploy App Service or AKS
• Configure continuous deployment
• Set up monitoring with Application Insights

Kubernetes on Any Cloud

• Install kubectl and helm
• Connect to cluster (update kubeconfig)
• Create namespaces for environments
• Apply RBAC policies
• Deploy applications (deployments, services)
• Configure ingress for external access
• Set up monitoring (Prometheus, Grafana)
• Implement GitOps with ArgoCD/Flux

CI/CD Pipeline (GitHub Actions)

• Create .github/workflows/deploy.yml
• Configure secrets (cloud credentials, API keys)
• Add build and test jobs
• Add container build and push to registry
• Add deployment job to cloud platform
• Set up branch protection rules
• Enable status checks and notifications

FinOps Cost Optimization

• Implement resource tagging strategy
• Enable cost allocation tags
• Set up budget alerts
• Analyze resource utilization (CloudWatch, Azure Monitor)
• Identify rightsizing opportunities
• Purchase reserved instances for predictable workloads
• Configure auto-scaling and scheduling
• Regular cost reviews and optimization

DevSecOps Security

• Add SAST scanning to CI/CD (SonarQube, Semgrep)
• Add dependency scanning (Snyk, Trivy)
• Implement container image scanning
• Set up secrets management (Vault, cloud provider)
• Configure security groups and network policies
• Enable audit logging
• Implement security monitoring and alerting
• Regular vulnerability assessments

Cloudflare Workers

• Install Wrangler CLI
• Create Worker project
• Configure wrangler.toml (bindings, routes)
• Test locally with wrangler dev
• Deploy with wrangler deploy

Docker

• Write Dockerfile with multi-stage builds
• Create .dockerignore file
• Test build locally
• Push to registry (ECR, ACR, GCR, Docker Hub)
• Deploy to target platform